Theoretical Foundations of Computer Vision

Computer Vision is a rapidly growing field of research investigating computational and algorithmic issues associated with image acquisition, processing, and understanding. It serves tasks like manipulation, recognition, mobility, and communication in diverse application areas such as manufacturing, robotics, medicine, security and virtual reality. This volume contains a selection of papers devoted to theoretical foundations of computer vision covering a broad range of fields, e.g. motion analysis, discrete geometry, computational aspects of vision processes, models, morphology, invariance, image compression, 3D reconstruction of shape. Several issues have been identified to be of essential interest to the community: non-linear operators; the transition between continuous to discrete representations; a new calculus of non-orthogonal partially dependent systems.

Attentive Visual Motion Processing: Computations in the Log-Polar Plane.- Invariant Thinning and Distance Transform.- Recognition of Images Degraded by Linear Motion Blur without Restoration.- Symmetric Bi- and Trinocular Stereo: Tradeoffs between Theoretical Foundations and Heuristics.- Surface from Motion—without and with Calibration.- Properties of Pyramidal Representations.- A Robust Approach to Estimation of Parametric Models.- Computer Vision and Mathematical Morphology.- A Variational Approach to the Design of Early Vision Algorithms.- Banach Constructor and Image Compression.- Piecewise Linear Approximation of Planar Jordan Curves and Arcs: Theory and Applications.- Segmentation with Volumetric Part Models.- Theoretical Foundations of Anisotropic Diffusion in Image Processing.- Stability and Likelihood of Views of Three Dimensional Objects.